Survival functions for defining a clinical management Lost To Follow-Up (LTFU) cut-off in Antiretroviral Therapy (ART) program in Zomba, Malawi.

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Rachlis B, Cole DC, van Lettow M, Escobar M,

Rachlis B, Cole DC, van Lettow M, Escobar M, (click to view)

Rachlis B, Cole DC, van Lettow M, Escobar M,

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BMC medical informatics and decision making 2016 05 0516(1) 52 doi 10.1186/s12911-016-0290-7

While, lost to follow-up (LTFU) from antiretroviral therapy (ART) can be considered a catch-all category for patients who miss scheduled visits or medication pick-ups, operational definitions and methods for defining LTFU vary making comparisons across programs challenging. Using weekly cut-offs, we sought to determine the probability that an individual would return to clinic given that they had not yet returned in order to identify the LTFU cut-off that could be used to inform clinical management and tracing procedures.

Individuals who initiated ART with Dignitas International supported sites (n = 22) in Zomba, Malawi between January 1 2007-June 30 2010 and were ≥ 1 week late for a follow-up visit were included. Lateness was categorized using weekly cut-offs from ≥1 to ≥26 weeks late. At each weekly cut-off, the proportion of patients who returned for a subsequent follow-up visit were identified. Cumulative Distribution Functions (CDFs) were plotted to determine the probability of returning as a function of lateness. Hazard functions were plotted to demonstrate the proportion of patients who returned each weekly interval relative to those who had yet to return.

In total, n = 4484 patients with n = 7316 follow-up visits were included. The number of included follow-up visits per patient ranged from 1-10 (median: 1). Both the CDF and hazard function demonstrated that after being ≥9 weeks late, the proportion of new patients who returned relative to those who had yet to return decreased substantially.

We identified a LTFU definition useful for clinical management. The simple functions plotted here did not require advanced statistical expertise and were created using Microsoft Excel, making it a particularly practical method for HIV programs in resource-constrained settings.

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